Is our obsession (particularly in the U.S.) with being special and unique bringing a dark side to our workplaces? Do people with issues and ideosyncracies make good leaders or bad ones? Are we all worrying about the wrong stuff?

Organizational psychologist and behavioral finance consultant Doctor Daniel Crosby tackles these and many other interesting examples in his TED video You're Not That Great! A Motivational Speech.

What lessons can those of us in HR - and particularly in the rewards field - draw from Dr. Crosby's talk?

Interested in obtaining your CCP (Certified Compensation Professional) designation, but don't have the funds or employer support to make it happen?

WorldatWork is offering one-year scholarship packages to obtain the CCP designation (or any of the other total rewards certifications offered by the Association). The application deadline is August 6.

The scholarships will be awarded based on financial need and merit and are open to any HR professional (you need not be a current WorldatWork member) from anywhere in the world. There is no fee to apply.

A client of mine with a gift for distilling information recently came up with a simple and elegant chart that tracks employee perceptions of the company's pay program. As someone who believes there is still a place for the straightforward, low-tech solution (like this one), I wanted to share a version of the chart here, for comment and reaction.

Essentially, it works like this. Employees go through a simple process where they rate the pay program on a scale of 1 through 10 (1 being the least favorable rating, 10 being the most) based upon their perception of it being "clear" and "fair." The results are shared in the form of a scatterplot, like the example I've created and shared below.

Big data it may not be, but it does provide a fundamental two-dimensional snapshot of what employees think about the pay program. It would also be interesting to:

Track movement over time, perhaps with an overlay of different marker colors to reflect different periods (quarters, years, etc.).

Separate by different employee variables/demographics, again potentially using different marker colors, such as gender, tenure, performance level, etc.

What do you think? Anybody done something similar - or similarly simple and elegant - that they can comment about?

Experimentation has been on my mind a lot lately. I am coming to believe that moving compensation (and all HR) programs and practices forward, at the ground level where most of us live and work, will happen through evidence-based learning and innovation, through tinkering and tailoring, and through raising the bar on our understanding of fundamental data analysis. With this in mind, I was happy to bump into the HBR article Step-by-Step Guide to Smart Business Experiments (registration required for full article) written by professors Eric T. Anderson of Northwestern's Kellogg School and Duncan Simester of MIT's Sloan School of Management. And happier still to borrow shamelessly from their material to create my own set of rules for compensation and HR experimentation, presented below.

Rule 1: Clarify the Question, Define the Concept

Any experiment begins, of course, by getting as clear as we can about what we are seeking to learn and the kind of evidence that will provide us an answer. In academia, as Anderson and Simester note, researchers typically change one variable at a time so that they can know exactly what caused an outcome. While ideal, in business this may not always be possible or practical. For this reason, the authors advocate instead a proof-of-concept approach where you "change as many variables in whatever combination you believe is most likely to get the result you want."

Rule 2: Set it Up Like a Scientist

A business experiment requires three things: a treatment group (where the compensation or HR action in question is "applied"), a control group (a complementary group with no action) and a feedback mechanism (which allows you to observe how those in each group respond). Feedback can come via data or metrics that measure the impact of the treatment on individuals in the group; this could include things like voluntary turnover, engagement survey results, productivity or operating statistics, etc. The feedback might also be drawn through more targeted survey efforts, through interviews or focus groups.

Rule 3: Don't Miss the Natural Experiments

The article quotes Norwegian economist Trygve Haavelmo, who won the 1989 Nobel prize, and observes that that there are two types of experiments: “those we should like to make” and “the stream of experiments that nature is steadily turning out from her own enormous laboratory, and which we merely watch as passive observers.” The point here is that we (as busy, overextended professionals) should learn to recognize and take advantage of the low-hanging fruit; experiments that are either already happening in our organizations or conditions that readily lend themselves to easy experimentation. Keep an eye out for treatment and control groups that may already exist, or are being created by factors outside your control.

Rule 4: Measure as Much as You Can

The more you measure, the more you may potentially learn. Slicing your data by different variable turns one experiment into many, while examining only aggregate data may cause you to miss things. You might look at your results by, for example, differences in tenure, performance, HQ versus field, income level and even demographics like age, gender, etc.

Rule 5: Keep Your Eye on the Goal

Some companies, Anderson and Simester note, mistakenly believe that the only useful experiments are the successful ones. The goal is not to conduct perfect experiments; the goal is not even (really) to vindicate your preferred policy direction. The goal is to learn and to position ourselves for better business decisions. The goal -- at the end of the day -- is to bring your leadership team data and evidence, rather than hopes and beliefs, about your compensation and HR recommendations.

There is a movement underfoot, particularly among start-up firms and profiled this week in a Wall Street Journal article, to open up business information that has traditionally been closely held. This includes not only financial and operating data but also information on individual hiring decisions, salary and bonus details, and employee performance appraisals.

While I remain conflicted about complete pay transparency, I do believe there are some basic conditions and ground rules that can be put in place to maximize the odds of "open salary" success.

How do we come to understand the conditions in which a bonus plan is likely to succeed or fail? How do we learn to read the landscape and understand the pain points that might be causing employees to feel that their salaries are unfair. When things go south (as they often do), was it the design, the implementation, the communication or something else that sent them there?

How do we learn in HR and Compensation? How does innovation and development in our fields happen? Does academia and research inform real-life practice ... or is it really the other way around?

And what do birds have to do with any of this?

The answers (or at least some answers) to these and other questions in my post today at the Compensation Cafe!

Today at the Huffington Post, Cara Woodson Welch (WorldatWork's VP of Policy and Public Affairs) opens with a gracious hat tip to my post and takes those thoughts in a new direction, wondering whether the record number of women in the 113th Congress might bring some change to the institution and its "old boys" workplace culture.

With record numbers of women in the 113th Congress, will we see more female chiefs of staff? More women Legislative Directors? Will having more women in leadership positions result in better workplace policies? Could all of that lead to a more functional workplace overall? Could it perhaps lead to less discord and less dysfunction?

No, I am not a Pollyanna, and I do realize that the field of politics lends itself to 24-hour workdays and an emphasis of work over other things in life. I also realize that outside the Beltway there is little sympathy for the workplace lives of those in Congress and congressional staffers. But I also know that the level of frustration with Congress is at an all-time high. Isn't it possible that if we change the "old boys" work culture, we might see it ripple into a more productive workplace? It certainly will be a facet of the 113th Congress that bears watching.

Why do so many of us get so bent out of shape about CEO compensation, but not about that of other relatively highly paid people?

That is the central question explored by Cornell University's Kevin Hallock in his December workspan column "research for the real world", where he compares the growth in pay at the 95th percentile (top 5 percent) for CEOs and average U.S. workers to that of athletes in Major League Baseball, the National Basketball Association, the National Football League and the National Hockey League. From 1995 to 2010, pay for this group of U.S. workers grew 69% while pay for the CEO group increased by 240% (one of those statistic that often provokes outrage). But pay for top NBA athletes also grew by 240% during that period, and top paid athletes from the other major sports is shown as growing at rates substantially above the U.S. worker (with the 95th percentiles of pay for the NFL, MLB and NHL players rising 200%, 175% and 125% respectively).

Why don't we hear comparable cries of outrage over those stats?

There are other fields of endeavor beyond business and sports where people are highly paid, and where the gap between average and top earners is similarly wide. As examples of this, we can consider some of the figures that Forbes provides us for top earners in acting, writing and music.

Tom Cruise, as the top paid actor on Forbes list, earned an estimated $75 million in 2011. His female counterpart, Kristin Stewart of Twighlight fame, earned an estimated $35 million.

The two highest paid authors, James Patterson and Stephen King, earned a healthy $94 million and $39 million, respectively.

In music, Sir Elton John topped the list at $100 million, with Lady Gaga close behind him at an estimated $90 million.

This when plenty of actors, writers and musicians are earning practically nothing.

Why do we find the high pay of one group of workers -- CEOs -- so much more inflammatory than the high pay of others? Kevin Hallock shares a few potential hypotheses in his column. Could it be that CEO salaries are simply better known and more widely reported? Is it because most people have a clear sense of the limits of their own athletic (or acting, writing or musical) abilities, where the "gifts and talents" a top executive brings to the table are harder for most of us to discern and appreciate?

About The Author

More Info HereCompensation consultant Ann Bares is the Managing Partner of Altura Consulting Group. Ann has more than 20 years of experience consulting with organizations in the areas of compensation and performance management.